Composer · investment strategy
by Composer Technologies · via Composer
A daily, rules‑based QQQ booster: buy 2x QQQ after sharp dips, hedge with volatility and anti‑beta when QQQ is overheated, and otherwise own QQQ unless the S&P 500 trend is weak—then rotate into BTAL.
Description from Composer
of the return and risk figures:as the source publishes them
What $10,000 would have become, from the strategy's own published history, against the S&P 500 over the same dates. The basis is labelled.
This strategy doesn’t publish a performance history we can chart.
Each rule is quoted word for word from the strategy's own documents.
No rules extracted from this strategy’s text yet.
2 positions as of 2026-10-19
: the platform's backtest holdings, not a client account.
Compares the stated rules with the holdings (or, where none are published, a mix estimated from returns), using tests fixed before any results were seen.
0.5% of weight in (IVV: 3.0%)
1 fund (SEC N-PORT, as of 2026-05-31) · : QQQ via QQQM
This strategy’s rules haven’t been extracted yet, so there’s no claim to compare with. The measurement is still shown. : 96% · 2026-10-19 ()
0.0% of weight in (SPY: 0%)
This strategy’s rules haven’t been extracted yet, so there’s no claim to compare with. The measurement is still shown. : 100% · 2026-10-19 ()
2 of 6 funds in its are : QLD, UVXY
This strategy’s rules haven’t been extracted yet, so there’s no claim to compare with. The measurement is still shown. : 100%
Strategies that share its Leveraged ETFs label, from other sources first, strongest risk-adjusted return first.
Composer Technologies · Composer
Composer Technologies · Composer
How much of what we look for this strategy has, and why anything is missing. Fields that don't apply to it aren't counted.
4 missing
The text the rules are quoted from, with where it came from.
Rebalanced daily. It reads a short‑term “heat” score (RSI: 0–100; high=hot, low=cold) on QQQ (big‑tech index fund).<br>- If QQQ is very hot (>79), buy crash insurance: if volatility’s heat is low (<40) buy UVXY; else split VIXY and BTAL.<br>- If QQQ is very cold (<30), buy 2x QQQ (QLD).<br>- Otherwise, hold QQQ while SPY (S&P 500) is above its 200‑ or 30‑day average; if not, hold BTAL.
A daily, rules‑based QQQ booster: buy 2x QQQ after sharp dips, hedge with volatility and anti‑beta when QQQ is overheated, and otherwise own QQQ unless the S&P 500 trend is weak—then rotate into BTAL.
Dynamic, daily-rebalanced strategy that outperforms the S&P in the out-of-sample period: 24.64% vs 21.81% annualized return; Calmar 1.81 with volatility hedges. Trade-off: larger drawdowns, slightly lower OOS Sharpe.
This simple strategy beats the QQQ
Every value on file, each labelled with its calculation basis and as-of date.
| Backtest final value (from $10,000) | $8.3M | 2026-10-19 | |
| Backtest regulatory fees | $12k | 2026-10-19 | |
| Backtest slippage cost | $110k | 2026-10-19 |
| AI categories (Composer) | leveraged etfs, market‑neutral, mean reversion, momentum (rsi), nasdaq‑100 focus, tactical allocation, trend following, volatility hedge (vix etfs) | ||
| Asset classes / instruments | equities |
| Logic complexity (node count) | 24 | 2026-10-19 | |
| Rebalance frequency | daily |
| Concentration (Herfindahl index, out-of-sample, as Composer reports it) | 0.99 | 2026-10-19 | |
| Ticker universe (assets the logic can hold) | show[ "BTAL", "QLD", "QQQ", "SPY", "UVXY", "VIXY" ] | 2026-10-19 |
| Alpha vs SPY, out-of-sample (out-of-sample) | -0.03 | 2026-10-19 | |
| Beta vs SPY, out-of-sample (out-of-sample) | 1.28 | 2026-10-19 | |
| Correlation (R) vs SPY, out-of-sample (out-of-sample) | 0.75 | 2026-10-19 |
| Remixes (copies) | 110 | 2026-10-19 | |
| Watchers | 26 | 2026-10-19 |
| Community review status | ACTIVE | 2026-10-19 |
| Backtest length | 3,781 | 2026-10-19 | |
| Out-of-sample length | 330 | 2026-10-19 | |
| Return, backtest period (annualized) (backtest) | 56.50% | 2026-10-19 | |
| Return, backtest period (cumulative) (backtest) | 83k% | 2026-10-19 | |
| Return, out-of-sample period (annualized) (out-of-sample) | 24.64% | ||
| Return, out-of-sample period (cumulative) (out-of-sample) | 32.85% | ||
| Return, trailing 1 day (out-of-sample) | -2.52% | 2026-10-19 | |
| Return, trailing 1 month (out-of-sample) | 4.99% | ||
| Return, trailing 1 week (out-of-sample) | -2.66% | 2026-10-19 | |
| Return, trailing 1 year (backtest) | 12.12% | 2026-10-19 | |
| Return, trailing 1 year (out-of-sample) | 16.14% | ||
| Return, trailing 2 weeks (out-of-sample) | -3.96% | 2026-10-19 | |
| Return, trailing 3 months (out-of-sample) | 7.23% | ||
| SPY annualized return over the backtest window (backtest) | 15.65% | 2026-10-19 |
| Calmar ratio, backtest period (backtest) | 2.62 | 2026-10-19 | |
| Calmar ratio, out-of-sample period (out-of-sample) | 1.81 | ||
| Maximum drawdown, backtest period (backtest) | -21.56% | 2026-10-19 | |
| Maximum drawdown, out-of-sample period (out-of-sample) | -13.61% | ||
| Sharpe ratio, backtest period (backtest) | 1.72 | 2026-10-19 | |
| Sharpe ratio, out-of-sample period (out-of-sample) | 1.17 | ||
| Sortino ratio, backtest period (backtest) | 3.23 | 2026-10-19 | |
| Sortino ratio, out-of-sample period (out-of-sample) | 1.57 | 2026-10-19 | |
| Standard deviation, backtest period (backtest) | 28.31% | 2026-10-19 | |
| Standard deviation, out-of-sample period (out-of-sample) | 20.61% |
| Annualized turnover, backtest period (backtest) | 20.93 | 2026-10-19 | |
| Annualized turnover, out-of-sample period (out-of-sample) | 22.91 | 2026-10-19 | |
| Daily win rate, backtest period (backtest) | 56.31% | 2026-10-19 | |
| Daily win rate, out-of-sample period (out-of-sample) | 53.94% | 2026-10-19 |
Composer Technologies · Composer
Composer Technologies · Composer
